Opening the paper…
Machine Learning Techniques, End Term
During classification of linearly separable data-set using perceptron algorithm, as the value of learning rate α is decreased,
During classification of linearly separable data-set using perceptron algorithm, as the value of learning rate α is decreased, A knn algorithm with *k* = 30 gives high training error and high validation error. What value of the *k* we should choose to get the better performance of the\ algorithm? Consider a binary classification problem. Let *p*1 denote the proportion of class 0 examples in a particular node. Which of the following graphs shows correct curves for the Gini-index, Entropy and misclassification error of that node?